Gumstix Jetson Nano/Xavier NX Snapshot Board

Out of stock
PKG900000001185
$279.00

The Snapshot is the ultimate edge AI video capture device, powered by the NVIDIA Jetson Nano or Xavier and control up to 16 1080p 30fps video streams into a single board.

Yocto image with built in TensorFlow support for Jetson Nano included. Xavier NX software is supported by the NVIDIA Jetpack 4.4DP.

IMPORTANT: To ensure compatibility make sure to use a Jetson Nano (V. B01 or newer) or the Jetson Xavier NX (V. A02 or newer).

Gumstix Jetson Nano/Xavier NX Snapshot Board Barrel ConnectorCamera ConnectorEthernetWiFi

Each Jetson Nano or Xavier NX supports up to four Raspberry Pi Camera Modules V2.

The Gumstix Jetson Nano/Xavier NX Snapshot board was designed with heavy support for video capture in mind, making it the perfect board for developing edge AI projects that require an abundance of cameras. Four Jetson Nano or Xavier NX Boards are interconnected via a Gigabit switch to allow for quick and easy communication. NVIDIA Jetson Boards and the switch can be remotely monitored and reset using the on-board ESP32 module. Realize your dream computer vision or robotics project by detecting, classifying, counting and tracking objects with the ability to control up to 16 1080p 30fps video streams on a single board. Utilize your board to train models for nearly any image or object recognition application, or for deploying pre-trained models for your specific purposes.

The Gumstix Engineering Team has created Yocto images with pre-integrated TensorFlow support for Jetson Nano Products for rapid and easy deployment.

This multi-camera Snapshot Board is a great way to scale your video edge AI project with the following:

  • 4 x Jetson Nano or Xavier NX Vertical Connectors
  • 16 x 15-pin Vertical Camera Connectors (Compatible with Raspberry Pi Camera Module V2)
  • RJ45 Jack with Gigabit Magnetics
  • Micro B USB Plug for flashing and another for serial debugging
  • ESP32 for Jetson Nano, power and switch management
  • Redundant WiFi backup connection for Ethernet failure
  • Serial debugging available via USB connector or via network management

Jetson Nano Heatsink now available at Gumstix online. Jetson Xavier NX Heatsink coming soon.

Important

To ensure compatibility make sure to use a Jetson Nano (V. B01 or newer) or the Jetson Xavier NX (V. A02 or newer).

Customize Your Board

Customize the Gumstix Jetson Nano Snapshot board to your project's specific needs in Upverter D2O. Add features or remove unused components with the ease of a drag-and-drop interface.

Included Components
Gumstix Jetson Camera Board

Uses NVIDIA Jetson Nano COM Vertical Connector as its COM/processor.

Functional modules include: RMII Bridge 5-Port Gigabit Switch Analog Devices ADG709 4-Channel Mux Ethernet Connector USB Micro-B Jack USB Micro-B Jack USB-UART USB-UART UART Bridge UART Bridge

Powered by a Barrel Connector (20V 3A).

Family Gumstix, Nvidia
Camera Connector

Vertical cable orientation connector for Raspberry Pi Camera.

Ethernet

10/100/1000 Base-T

Processor

Quad-core ARM® A57

RAM

4 GB 64-bit LPDDR4

USB Device

Micro B USB Plug

WiFi

802.11 b/g/n wireless communications.

Gigabit Ethernet Switch

7-Port (5xPHY + 2xRGMII)

GPU

128-core NVIDIA Maxwell™ architecture-based GPU

Barrel Connector

Industry standard barrel connector

Key Components
RJ45 Jack with Gigabit Magnetics

RJ45 Jack with Gigabit Magnetics

Specs
Micro B USB Plug

Micro B USB Plug

2.0 mm 20V DC Power Jack

2.0 mm 20V DC Power Jack

FTDI FT232RQ USB UART Interface

Connect to an RS232 serial terminal over USB with the FTDI FT232RQ interface

Specs
SMD Module, ESP32-D0WD, 32MBITS Flash, U.fl Connector

SMD Module, ESP32-D0WD, 32MBITS Flash, U.fl Connector

Specs
Mating Connectors

Please read the instructions in the README file carefully before starting. Instructions and functions are explained in the file.

Files that are needed (such as bootloader and operating system) to create a bootable disk image, are available below.

Our Support page links additional resources.

Software Version: